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A shallow depth of eld can be employed by selecting an aperture of f/5.6 and under when you only want a small part of the scene or plane of focus to be sharp in the nal image. A shallow depth of eld is very useful for separating your subject from a busy or distracting background. The widest aperture on your lens provides the shallowest depth of eld and is often referred to as shooting wide open. You can further reduce the DOF by moving in closer to your subject, moving your subject farther away from the background, or switching to a longer focal length lens.

Besides offering Web-based training courses, Techsity University also provides instructor-led training courses. To enhance and test the learning of students, the trainers in the university have unanimously agreed to send a weekend assignment to students every week. Catherine, a Web site designer, is assigned the task of preparing a form on the Web site. A student should be able to enter personal details in the form and upload an assignment to the university s Web server. The details in the form should include student ID, student name, course ID, and assignment number. After a student clicks the Submit button on the form, these details and the file uploaded should appear on the next screen in the browser. The student should also be able to go back to the form and view the details previously entered.

Another common application is a small PV array that uses inverter-based interconnection systems. These systems are typically less than 10 kW. A functional diagram is given in Figure 14.6. Some state public utility commissions require utilities to

where f j is the operator over the image window x, pj a parity sign, changing the inequality direction, and j a classi cation threshold. Such a classi er, even after training over the entire sample set xi , will not have a good classi cation performance because more or less, half of the sample is misclassi ed; however, a cascade of two classi ers with AdaBoost training produces an acceptable detection rate. Open-source libraries for computer vision, such as OpenCV [15], contain ef cient implementations of both AdaBoost training and detection functionalities. After performing face detection on a stereo camera setup, image locations can be used as a feature-level measurement so that the state-space localization can be done by triangulation. Figure 6.4 shows an example of face detection and three-dimensional localization, with stereo triangulation based on the DLT [77]. This method can easily be extended to multiple targets by additionally matching face pairs (data association) of different people across stereo images with a simple template matching.

In order to make an informed decision concerning what type of ash lighting system to purchase, you have a few other considerations that should be addressed as well. Only you can decide which system best meets your shooting needs. The following sections provide more information on all three of these systems and their advantages for particular types of shooting.

It typically doesn t occur to most Excel users to automate Access using Excel. Indeed, it s difficult for most to think of situations where this would even be necessary. Although there are admittedly few mind-blowing reasons to automate Access from Excel, you may find some of the automation tricks found in this section strangely appealing. Who knows You may even implement a few of them.

This example uses a simple loan to demonstrate the basic concepts involved in creating a dynamic schedule. Refer to the worksheet in Figure 13-1.

/****************************************************************************** CoxIngersollRoss : Constructor [in] Rate r0 : initial risk-free rate double theta : theta paramater double k : k parameter for Feller condition double volatility : volatility of short rate ******************************************************************************/ CoxIngersollRoss::CoxIngersollRoss(Rate r0, double theta, double k, double sigma) : OneFactorAf neModel(4), theta_(arguments_[0]), k_(arguments_[1]), sigma_(arguments_[2]), r0_(arguments_[3]) { theta_ = ConstantParameter(theta, PositiveConstraint());

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